Certain embodiments of the present invention relate to ultrasound imaging of the human anatomy for the purpose of medical diagnosis. In particular, certain embodiments of the present invention relate to methods and apparatus for assessing tissue motion and deformation, and for improving the assessment of myocardium performance.
The assessment of the myocardium (heart muscles) function using echo-cardiography, or ultrasound, is a crucial indication in the diagnosis of a patient. The outcome of the myocardium evaluation may significantly influence the patient management and course of treatment.
The main part of the myocardium evaluation is based on the observations of experienced echo-cardiographers, who evaluate myocardial dynamics using B-mode ultrasound imaging during a live scan or using a playback of stored cine-loops. The state of each myocardial segment is estimated according to its temporal dynamics. An experienced echo-cardiographer is often able to visually distinguish between working (viable) myocardial segments and segments with different pathologies.
There are disadvantages to relying on visual distinguishing, however. For example, the estimate may be qualitatively flawed as it is based on an impression from moving images. Also, the examination is significantly affected by intra/inter observer variations of diagnostic quality and reproducibility. Thus, the ultrasound may be affected by differing image quality and/or technique. Additionally, significant time is required to achieve the necessary proficiency enabling an echo-cardiographer to reach an accurate diagnosis, and the echo-cardiographer's skills may be negatively impacted if the examination is not performed on a routine basis.
Several quantitative methods exist for heart muscle assessment, such as color kinesis and tissue velocity imaging (TVI). The color kinesis approach is built on B-mode image processing. Automatic edge detection of the left ventricle (LV) allows the estimation of the inward/outward regional translations of the LV wall. This information can be shown in color-coded mapping and can be used for estimating regional myocardial viability. Several drawbacks of color kinesis are that it has limited capabilities to quantify the inner wall performance, and that it does not provide two-dimensional movement and contractility assessment.
TVI is also known as Doppler Velocity Imaging. TVI is based on the Doppler velocity measurements in different locations within a region of interest (ROI). TVI presents a color-coded velocity map of the regional tissue segments. A temporal graph of the mean velocity value of each interrogated point can be shown as well. Further calculations allow the estimation of the local contracting/stretching information which is considered to be a good indicator of the muscle viability. The contractility is presented in color-coded strain and strain rate maps as well as in a graphical form. TVI and its derivatives, strain and strain rate, have been a promising quantitative tool for the viability assessment of the regional myocardium segments, thereby improving the sensitivity and accuracy of inexperienced echo-cardiographers.
TVI, however, also has limitations. The basic TVI imaging shows colorized maps of tissue velocities, but the colorized maps are complicated and therefore difficult to understand. Also, the tissue velocity mapping does not provide the local contractility of the myocardium. The TVI derivatives, strain and strain rate imaging, are regional indicators. Unfortunately the low signal-to-noise ratio experienced with strain and strain rate imaging may not allow stable results.
Furthermore, the Doppler-based methods take temporal information from static Cartesian coordinates. The temporal measurements may mislead the echo-cardiographer because the tissue moves in time, and thus the measurements are made each time in a different location in the tissue.
Finally, the fundamental limitation with Doppler-based methods is that all Doppler methods are one-dimensional. Only the velocity component, which is parallel to the ultrasound scan direction, can be measured. Therefore, it is difficult to assess myocardial regions moving across or almost across ultrasound beams. For example, the assessment of a portion of the apical part of the left ventricle is almost impossible due to a large angle between the ultrasound scan direction and tissue velocity.
Therefore, improving the accuracy of heart muscle assessment by making the assessment more objective and quantitative would have a significant benefit. Also, having a method available for verifying the results of the assessment is desirable.